34 results about "Resource pricing" patented technology

The embodiment of the invention provides a billing method, an analysis center and a billing center. The billing method includes the steps that the analysis center inquires the zone corresponding to each lessee and the usable area, corresponding to the lessee, in each zone according to the mark of each lessee, at least one usable area corresponding to each lessee is obtained, the project corresponding to each lessee is inquired according to the mark of the lessee, the resource information of resources used by each lessee are inquired under the usable areas corresponding to the lessee, and the use amounts of the resources are counted; finally, the resource use information of each lessee is obtained, a resource use statistic summary table is generated and sent to the billing center, and the billing center obtains the resource use information of each lessee according to the resource use statistic summary table, and determines the expenses of each lessee according to a resource price list and the resource use information of the lessee. The use of various cloud service resources can be billed in a mixed mode, and multiple cloud platforms in the multiple zones can be billed in a mixed mode.

The invention discloses a log analysis service method characterized by charging according to cloud service resources. The method comprises the following steps of (1) pricing cloud service resources including at least one of the bandwidth, the storage time and the storage capacity; (2) and limiting the log analysis service of a user when the cloud service resources used by the user exceed a set standard. The log analysis service method characterized by charging according to cloud service resources makes very flexible charging means realized. Different popularization stages of various log cloud services can be flexibly used. For example, a traffic packet means can be used for allowing users.

The invention relates to an augmented Lagrangian-based resource consultation mechanism in MANETs (mobile ad hoc networks). The augmented Lagrangian-based resource consultation mechanism includes breaking down the ubiquitous service of a system optimization and balance framework, composed of multi-user and a network, into multiple atomic services; defining agents of various types, establishing and solving a resource pricing model; describing the information intersection in the resource market through the augmented Lagrangian-based resource consultation mechanism. By the use of the augmented Lagrangian-based resource consultation mechanism, user and network benefits can be comprehensively considered, and at the premise of the limited resource, maximum benefits of the whole network is achieved while the serve quality is ensured; multi-user benefits are balanced under the competitive environment, increasing of some user benefits never causes decreasing of other user benefits, with an iterative process, buyer bidding and seller offering are constantly adjusted, and the optimal resource allocation is achieved under the adjustment and control of the resource market.

The invention is applicable to the cloud computing technical field, and provides a resource pricing method based on Pareto optimization under the cloud environment. The method comprises the followingsteps: S1, based on user satisfaction degree and maximum utility of cloud service provider profit, establishing a Pareto optimization cloud service resource pricing model; S2, Pareto optimization is found based on hybrid search algorithm, that is, the best pricing of each cloud service resource is obtained. The invention proposes a resource pricing model based on Pareto optimality, and transformsthe price contradiction into a game between user satisfaction and cloud service provider profit, and finally realizes the balance between user satisfaction and cloud service provider profit, namely realizes Pareto optimality, and obtains the best pricing of each cloud service resource.

The invention discloses a method and apparatus for dynamically regulating pricing on a data inquiry operation. The method comprises: when detecting that distributed resource information of computing resources is changed, acquiring the distributed resource information of each type of computing resources in different time periods; acquiring fixed parameter information of each type of computing resources, wherein the fixed parameter information comprises total resource information of each type of computing resources in different time periods, lowest price information of each type of computing resources in different time periods and highest price information of each type of computing resources in different time periods; according to predetermined computing resource pricing regulating rules, the distributed resource information and the fixed parameter information, regulating pricing information of each type of computing resources in different time periods. Visibly, in the embodiment, the distribution condition of the computing resources is considered, and according to the distributed resource information of each type of resources in different time periods, pricing on the data inquiry operation is dynamically regulated, so that the data inquiry operation is more reasonably priced.

The invention discloses an SDN resource pricing method based on multi-ownership combinatorial double auction. The method comprises the following steps that the parameters of various variables of service chains and resources of an SDN resource system are determined, and resource proxies decompose multi-ownership service chains transmitted by nodes into buying and selling type service chains; the nodes meeting market benefit maximization are solved, and the resource proxies arrange different types of nodes in corresponding sequence tables; an average pricing matrix of transaction is obtained through ordering; a transaction price matrix QUOTE<TT> under the SDN environment is calculated by using a K-pricing scheme; the transaction process is determined, and pricing of the resources is performed according to the relationship between supply and demand of the resources; and total cost and revenue in buying or selling the resources can be obtained. The method is more suitable for the SDN environment and can alleviate problems faced by the SDN resources by utilizing the multi-ownership of a combinatorial double auction model and an SDN resource transaction market.

A method for cloud disaster recovery data backup based on a game theory relates to the technical field of data backup disaster recovery, and solves the problems in an existing data backup method that the resource cost is high, the storage cost is high, and influences of behaviors of source end cloud suppliers on a target end cloud supplier are neglected. The method for optimal data backup in a cloud disaster recovery environment based on the game theory provided by the invention is characterized in that interaction between the source end cloud supplier and the target end cloud supplier is simulated into a storage resource pricing model; and storage resource leading courses among backup nodes of the target end cloud supplier are modeled into a gaming course which pursues maximum benefits. The invention also provides a method for quantitative computation of optimal solutions of a storage resource quantity and a storage resource price, so that benefits of both gaming parties, namely the source end cloud supplier and the target end cloud supplier can be maximized simultaneously.

The embodiment of the invention provides a billing method, an analysis center and a billing center. The billing method includes the steps that the analysis center inquires the zone corresponding to each lessee and the usable area, corresponding to the lessee, in each zone according to the mark of each lessee, at least one usable area corresponding to each lessee is obtained, the project corresponding to each lessee is inquired according to the mark of the lessee, the resource information of resources used by each lessee are inquired under the usable areas corresponding to the lessee, and the use amounts of the resources are counted; finally, the resource use information of each lessee is obtained, a resource use statistic summary table is generated and sent to the billing center, and the billing center obtains the resource use information of each lessee according to the resource use statistic summary table, and determines the expenses of each lessee according to a resource price list and the resource use information of the lessee. The use of various cloud service resources can be billed in a mixed mode, and multiple cloud platforms in the multiple zones can be billed in a mixed mode.

The invention discloses a demand side resource pricing method and system based on shared random optimization. The method comprises the following steps: firstly, calculating the microgrid operation cost under the condition of having or not having demand response for each scene in N randomly generated scenes; calculating the income of the microgrid operator according to the microgrid operation costunder the demand response and the demand-free response, sorting the income under the N scenes from large to small, and selecting the income without money loss for ensuring that the island microgrid operator does not lack money; and determining a demand side response price according to the money-loss-free income. A microgrid operator responds to resource pricing for a demand side. According to theinvention, the pricing of the demand-side resources is carried out by referring to the improvement condition of the power grid operation benefit after the demand-side response is introduced without considering a utility function or a comfort function, thereby guaranteeing the stable operation of the microgrid, attracting the user to participate in the demand-side response at a higher price, and enabling the pricing to be more reasonable.

The invention discloses a statistical analysis method for cloud computing resource pricing, comprising the following steps: step 1, given a resource instance of a new cloud service provider, and collecting cloud computing instances in the current market; step 2, counting The probability distribution of all current instances in different price ranges; step 3, standardize the data of current instances and new instances, and classify the current instances and new instances, and select the current instance in the same category as the new instance as the new instance Similar instances; step 4, obtain the initial market share of similar instances, and establish a user transition probability matrix, and use the Markov chain method to calculate the short-term market share and final market share of similar instances; step 5, calculate the price and probability of similar instances Distribution and market share, calculate the price of new instances.

The invention discloses a multi-dimensional resource pricing method in a mobile cloud computing environment based on a bilateral market. The method runs in the mobile cloud computing environment, the method involves two groups of participants in the mobile cloud computing environment, one group of participants are Cloudlets which have resources, and the other group of participants are VMs which request the resources. The VMs are regarded as a buyer in a bilateral market economic model, the Cloudlets are regarded as a seller, and the two sides complete allocation of the resources through a price interactive mechanism, unloading execution of an application request from the VMs to the Cloudlets is completed, and energy consumption of the mobile equipment is reduced. The price interactive mechanism in the method is based on a bilateral market game and is designed through combination of a punishment pricing mechanism and a balanced utility discount, the multi-dimensional resources of the application request of a mobile user can be reasonably distributed and dispatched on a plurality of Cloudlets, and therefore system benefits of a mobile cloud are maximized.

The invention relates to an augmented Lagrangian-based resource consultation mechanism in MANETs (mobile ad hoc networks). The augmented Lagrangian-based resource consultation mechanism includes breaking down the ubiquitous service of a system optimization and balance framework, composed of multi-user and a network, into multiple atomic services; defining agents of various types, establishing and solving a resource pricing model; describing the information intersection in the resource market through the augmented Lagrangian-based resource consultation mechanism. By the use of the augmented Lagrangian-based resource consultation mechanism, user and network benefits can be comprehensively considered, and at the premise of the limited resource, maximum benefits of the whole network is achieved while the serve quality is ensured; multi-user benefits are balanced under the competitive environment, increasing of some user benefits never causes decreasing of other user benefits, with an iterative process, buyer bidding and seller offering are constantly adjusted, and the optimal resource allocation is achieved under the adjustment and control of the resource market.

The invention discloses a renewable energy allocation algorithm based on Stackelberg game. The algorithm comprises the steps that (1) an energy supplier in a backhaul link set a suitable energy price, (2) an operator sets an order quantity and service cost according to the energy price, (3) the energy suppliers of nodes form an alliance, the step (1) and (2) are repeated to reaches a stable alliance structure. Compared with the prior art, through analyzing a user sensitivity to a data flow price and energy bidding of a renewable energy supplier, a wireless operator makes decisions about a flow requirement amount and a service price, through designing a distributed algorithm, the price of the energy supplier reaches an optimal price in a current competition situation, and the income of each part of a system is improved further through analyzing a cooperation mode.

The invention discloses a resource processing method and device, and a value conversion method and device. The resource processing method comprises the following steps of receiving a resource processing instruction; responding to the resource processing instruction and acquiring a first resource value and a first conversion coefficient; according to the ratio of the first resource value and the first conversion coefficient, acquiring a second conversion coefficient; according to the ratio of the first resource value and the second conversion coefficient, acquiring a second resource value. Thevalue conversion method comprises the following steps of receiving a value conversion instruction; responding to the value conversion instruction and acquiring a total resource value and the resourcepricing value of a platform in the previous day; and according to the ratio of the total resource value and the resource pricing of the platform in the previous day, acquiring the current integral pricing value of a commodity. In the method of the invention, the second resource value and the first resource value can be maintained to be consistent, simultaneously, the current integral pricing valueof hte commodity is acquired, resource processing and value conversion efficiency is increased, and simultaneously, the value of the commodity is accurately embodied.